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Meteorological forecasting is an important issue in research. Typically, the forecasting is performed at " global level, " by gathering data in a large geographical region and by studying their evolution, thus foreseeing the meteorological situation in a certain place. In this paper a " local level " approach, based on time series forecasting using Type-2(More)
– Meteorological forecasting is an important issue in research. Typically, the forecasting is performed at " global level " , by gathering data in a large geographical region and by studying their evolution, thus foreseeing the meteorological situation in a certain place. In this paper a " local level " approach, based on time series forecasting using(More)
Weather forecast are a typical problem where a huge amount of data coming from different types of sensors must be elaborated by means of complex, time-consuming algorithms. This work presents a new approach where the data fusion is performed with soft computing techniques. A statistical-neural system is used to "nowcast" meteorological data measured by a(More)
This paper presents a reliable ice detection and forecasting system based on a special road weather information system and a data processing algorithm for ice event forecasting. The ice detection system is mainly based on two innovative sensors, developed ad hoc for this particular application; namely an ice sensor for the reliable detection of accumulation(More)
The research activity described in this paper concerns the study of the phenomena responsible for the urban and suburban air pollution. The analysis carries on the work already developed by the NeMeFo (Neural Meteo Forecasting) research project for meteorological data short-term forecasting, Pasero (2004). The study analyzed the air-pollution principal(More)
In this paper an " intelligent systems " based on neural networks and a statistical non parametric method evaluates the future evolution of meteorological variables and the occurrence of particular phenomena such as rain and road ice. The meteorological variables forecast system is based on a recurrent feed forward multi layer perceptron which make the(More)
The study described in this paper, analyzed the urban air pollution principal causes and identified the best subset of features (meteorological data and air pollutants concentrations) for each air pollutant in order to predict its medium-term concentration (in particular for the PM 10). An information theoretic approach to feature selection has been applied(More)
The study described in this paper, analyzed the urban and suburban air pollution principal causes and identified the best subset of features (meteorological data and air pollutants concentrations) for each air pollutant in order to predict its medium-term concentration (in particular for the PM 10). An information theoretic approach to feature selection has(More)
The research activity described in this paper concerns the study of the phenomena responsible for the urban and suburban air pollution. The analysis carries on the work already developed by the NeMeFo (neural meteo forecasting) research project for meteorological data short-term forecasting. The study analyzed the air pollution principal causes and(More)